Bike Rental Dashboard Lab 6
bike_data$tooltip_text <- paste("Season:", bike_data$season,
"<br>Total Rentals:", bike_data$cnt)
p_bar <- ggplot(bike_data, aes(x = factor(season), y = cnt, fill = factor(season), text = tooltip_text)) +
geom_bar(stat = "identity") +
labs(title = "Total Bike Rentals Across Seasons", x = "Season", y = "Total Rentals") +
theme_minimal()
ggplotly(p_bar, tooltip = "text")bike_long <- bike_data %>%
select(dteday, casual, registered, yr) %>%
pivot_longer(cols = c(casual, registered), names_to = "user_type", values_to = "count")
p <- ggplot(bike_long, aes(x = dteday, y = count, color = user_type, frame = yr, text = paste("Date: ", dteday, "<br>User Type: ", user_type, "<br>Count: ", count))) +
geom_point(size = 1) +
scale_color_manual(values = c("registered" = "blue", "casual" = "red")) +
labs(title = "Casual vs Registered Users Over Time", x = "Date", y = "Count") +
theme_minimal()
# Make it interactive and animated
ggplotly(p, tooltip = "text") %>% animation_opts(frame = 1000, easing = "linear")p_facet <- ggplot(bike_data, aes(x = dteday, y = cnt, color = factor(season))) +
geom_line() +
facet_wrap(~ season, scales = "free_y") +
labs(title = "Bike Rentals Trends by Season", x = "Date", y = "Total Rentals") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplotly(p_facet)